FAQ

FAQ

Class Readiness

Computer Configuration

  • Processor:
    x64-based processor, x64 based architecture (Intel Core-i3/i5/i7)
    Please Note: ARM Architecture Based Processor (like Snapdragon X Elite) not support Microsoft SQL Server.
  • Operating System:
    64-bit operating system, Windows 10 Pro, Windows 11 Pro (Recommended)
  • RAM: 4 GB, 8 GB (Recommended)
  • Hard Drive: SSD, NVMe (Recommended)
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Download/Install Necessary Software

SQL Server 2025 Developer Edition & SQL Server Management Studio (SSMS)

Get the full-featured free edition, licensed for use as a development and test database in a non-production environment.

Click here to Download SQL Server 2025

Click here to Download SSMS

Click here for Instruction

Power BI Desktop

Create rich, interactive reports with visual analytics at your fingertips—for free.

Click here for Instruction

Visual Studio 2026 Community Edition

A fully-featured, extensible, free IDE for creating modern applications for Android, iOS, Windows, as well as web applications and cloud services.

Click here to Download

Click here for Instruction

Anaconda Navigator for Data Science

Launch data science applications from your desktop with Anaconda Navigator, Terminal Window Not Required.

Click here for Instruction

Download Necessary Dataset

SQL/TSQL Tools

HR Dataset Emp
World Population

Explore the World Population Through Data
Discover population, economy, health, and more with the most comprehensive global statistics at your fingertips.

Click here to Download

HR Database Dept
Brazilian E-Commerce
HR Database 05
Oscar Dataset
Sakila Database
Northwind Database

Download Necessary Dataset

Power BI Tools

Sales Data (.csv)

Use this dataset aims to analyze sales data over multiple years to identify key trends, customer behavior, product performance, and regional sales distribution. By leveraging structured business data, we can generate insights that support decision-making, improve operational efficiency, and enhance overall business strategy.

Click here for Download

Sales KPI

A sales KPI dashboard is a visual tool that consolidates key performance indicators (KPIs) into interactive charts and graphs to provide a real-time, at-a-glance view of sales team performance against goals.

Click here to Download

Sales Data (.xls)

Use this dataset aims to analyze sales data over multiple years to identify key trends, customer behavior, product performance, and regional sales distribution. By leveraging structured business data, we can generate insights that support decision-making, improve operational efficiency, and enhance overall business strategy.

Click here for Download

London & Boston Data (.txt)

A sales KPI dashboard is a visual tool that consolidates key performance indicators (KPIs) into interactive charts and graphs to provide a real-time, at-a-glance view of sales team performance against goals.

Click here to Download

Forecast Dataset

A forecast dataset contains historical and present information used to predict future outcomes, and examples include sales data for forecasting revenue, weather observation data for predicting weather patterns, and retail inventory data for anticipating demand.

Click here to Download

Forecast Dataset

A forecast dataset contains historical and present information used to predict future outcomes, and examples include sales data for forecasting revenue, weather observation data for predicting weather patterns, and retail inventory data for anticipating demand.

Click here to Download

Download Necessary Dataset

Python for Machine Learning

House Price

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.

Click here for Download

Clean Table

Clean Table Dataset

Click here for Download

House Price

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.

Click here for Download

House Price

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.

Click here for Download

House Price

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.

Click here for Download

House Price

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.

Click here for Download

Download Necessary Dataset

Advanced Excel

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

Master Database

All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.

Click here for Download

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